Exudate analysis using optical signatures

ABSTRACT

Disclosed techniques include exudate analysis using optical signatures. Access to a tissue exudate sample is obtained, wherein the tissue exudate sample contains one or more analytes representing a state of the tissue. The one or more analytes are isolated from the exudate sample on a substrate. The exudate is transferred from the substrate to an immunoassay. The immunoassay is illuminated with photons, wherein the illuminating comprises a controlled photon exposure. The controlled photon exposure comprises ambient lighting and/or one or more fluorescence excitation light wavelength bands. Light emanating from the immunoassay is imaged, wherein the imaging captures intensities of light wavelengths across the light wavelength spectrum. The imaging captures reflected light and fluorescent emanating light. A signature for the one or more analytes is generated, based on analysis of the intensities that were imaged. The signature expresses a magnitude for each of the one or more analytes.

RELATED APPLICATIONS

This application claims the benefit of U.S. provisional patent applications “Systems and Methods for Wound Care Diagnostics and Treatment” Ser. No. 62/964,969, filed Jan. 23, 2020, and “Multispectral Sample Analysis Using Fluorescence Signatures” Ser. No. 63/132,541, filed Dec. 31, 2020.

Each of the foregoing applications is hereby incorporated by reference in its entirety.

FIELD OF ART

This application relates generally to exudate analysis and more particularly to exudate analysis using optical signatures.

BACKGROUND

People use a wide variety of materials for all kinds of purposes. In fact, materials are pervasive throughout the world. We wear items of clothing made from materials to protect us, to keep us warm, and to make statements about ourselves and our beliefs. We live in temporary or permanent structures constructed from materials, and travel in vehicles made from materials, to name only a very few uses of materials. A material is a substance or a mixture of substances that make up a given object. A few often-used examples of materials include wood, plastics, metals, fabrics, and glass. The materials that are commonly used include naturally occurring materials and synthetic materials. The materials can be used in their pure form such as wood or iron, or can be used in an “impure” or combined form. In this context, an impure form of a material can include a compound, a composite, or a blend of materials. A material or combination of materials can usually be identified by studying various properties of the material in question such as how hard the material is, what it looks like, and how much it weighs. Material properties that are of particular interest include physical properties such as state, where the material state includes solid, liquid, gas, or plasma. Other physical properties include the density of the material and magnetic characteristics of the material. The material properties of interest further include chemical properties such as the chemical resistance of the material to attack by other chemicals, and the combustibility of the material. The material properties can further include mechanical properties such as malleability, ductility, and strength; and electrical properties such as conductivity and resistivity. The properties of a material can additionally include optical properties such as transmissivity and absorptivity. Still other properties can also be used. Because each material has its own unique set of properties, the physical, chemical, mechanical, electrical, optical, and other responses of a material can be analyzed to characterize and identify unknown materials.

Analyzing and characterizing materials is widely applied in many industries including manufacturing, aerospace, and taxonomy, to name but a few. The analysis and characterization of materials is also widely used in research applications to identify a material or materials within a sample, to characterize new alloys or compounds of materials, and so on. The analysis and characterization of materials can also be used to identify materials that should not be present within a sample. Some applications include identifying contaminants or impurities within materials, where the contaminants cause systems made from the materials to fail. Sophisticated tests and techniques can provide detailed information about a material, such as identifying its chemical composition, without which the tests and techniques would be a very challenging task. This latter class of analysis can require complex laboratory equipment and testing techniques. For example, a scanning electron microscope (SEM) uses a beam of electrons to reveal information about the surface topology and composition of a material, while a transmission electron microscope (TEM) can be used in crystalline defect analysis to predict behavior and to find failure mechanisms for materials. Also, X-ray Diffraction (XRD) is used to identify and characterize crystalline materials. These complicated and expensive tests, techniques, and types of equipment, usually available only in laboratories, can be used alone or in combination to characterize and identify unknown materials.

SUMMARY

Disclosed techniques can characterize and identify analytes in a material sample which includes exudate by illuminating the sample with a controlled photon exposure and imaging the light emanating from an immunoassay of the exudate. The techniques disclosed herein illuminate a sample with a controlled photon exposure, where the photons can include a range of wavelengths across the electromagnetic spectrum. The range of wavelengths correspond to various types of light such as infrared (IR) light, long-wavelength IR (LWIR) light, visible light, ambient light, fluorescence excitation light wavelength bands, and so on. The wavelengths can also include those that correspond to thermal energy. A light source excites electrons in molecules of a compound and causes the electrons to emit light or to fluoresce. In addition, materials reflect and absorb light differently at different wavelengths. Thus multispectral imaging can be used to differentiate materials based on their spectral fluorescence signatures, in addition to their reflection and absorption characteristics. As disclosed, exudate analysis using optical signatures can reduce the complexity, cost, and deployment challenges of using specialized cameras, elaborate optical filters, and expensive filter wheels which have orientation and alignment sensitivities and employ fixed, lab-only equipment placement.

Disclosed techniques address a method for exudate analysis using optical signatures. The disclosed techniques enable handheld, portable, multispectral material sample analysis. Access to a tissue exudate sample is obtained, where the tissue exudate sample contains one or more analytes representing a state of the tissue. The wound exudate can be obtained from a bandage associated with a patient, beneath a film covering a wound, from a negative pressure system, and so on. The one or more analytes are isolated from the exudate sample on a substrate. The isolating can be used to isolate further constituents within the exudate such as both analytes and colonizing microbial agents. The isolating can be used to determine which analytes are present as well as the one or more varieties of colonizing microbial agents. Determining the analytes is critical to diagnosing the wound state. Determining the microbial agents is critical to effective treatment of the wound. The isolating can be accomplished using a variety of techniques which may include using a lateral flow assay, associating the one or more analytes to one or more light emitting markers, and the like. The exudate is transferred from the substrate to an immunoassay. The immunoassay can be a system of lateral flow assays, enzyme-linked immunosorbent assays (ELISA), or multiplexed assays using encoded particles. The exudate that was obtained can be transferred to the substrate using a transfer foam or woven material. The transferring of the exudate from the substrate to an immunoassay can be performed using a cartridge to apply mechanical pressure to extract the exudate from the substrate. The immunoassay is illuminated with photons, where the illuminating comprises a controlled photon exposure. The controlled photon exposure can include ambient lighting on the substrate, one or more fluorescence excitation light wavelength bands, and so on. Light emanating from the immunoassay is imaged, where the imaging captures intensities of light wavelengths across the light wavelength spectrum. The imaging captures reflected light, fluorescent emanating light, etc. A signature is generated for the one or more analytes, based on analysis of the intensities that were imaged. The signature expresses a magnitude for each of the one or more analytes. A wound assessment is generated based on the signature. The signature can also be used to model tissue wound healing, to generate a tissue treatment plan, and so on.

A method for exudate analysis is disclosed comprising: obtaining access to a tissue exudate sample, wherein the tissue exudate sample contains one or more analytes representing a state of the tissue; isolating the one or more analytes from the exudate sample on a substrate; transferring the exudate from the substrate to an immunoassay; illuminating the immunoassay with photons, wherein the illuminating comprises a controlled photon exposure; imaging light emanating from the immunoassay, wherein the imaging captures intensities of light wavelengths across the light wavelength spectrum; and generating a signature for the one or more analytes, based on analysis of the intensities that were imaged.

Various features, aspects, and advantages of various embodiments will become more apparent from the following further description.

BRIEF DESCRIPTION OF THE DRAWINGS

The following detailed description of certain embodiments may be understood by reference to the following figures wherein:

FIG. 1 is a flow diagram for exudate analysis using optical signatures.

FIG. 2 is a flow diagram for isolating.

FIG. 3 shows a system block diagram for diagnosis and treatment.

FIG. 4 is a table for identifying infection.

FIG. 5 is a system block diagram for infection locating.

FIG. 6 is a system block diagram for dermis healing.

FIG. 7 is a system block diagram for antibody detection.

FIG. 8 illustrates an antibody array.

FIG. 9 shows images for infection detection and analysis of wound state.

FIG. 10 is a table showing biochromes and fluorescent channels.

FIG. 11 is a table showing cells associated with hemostasis and wound healing.

FIG. 12 is a table showing immune surveillance cells.

FIG. 13 shows granulation identification.

FIG. 14 illustrates water identification.

FIG. 15 shows blood vessel identification.

FIG. 16 illustrates tissue oximetry.

FIG. 17 shows a diagram for a substrate isolating analytes from an exudate sample in one step.

FIG. 18 shows a diagram for a substrate isolating analytes from an exudate sample in two or more steps.

FIG. 19 is a system diagram for exudate analysis using optical signatures.

DETAILED DESCRIPTION

Techniques for exudate analysis based on optical signatures are disclosed. Access to a tissue exudate sample is obtained, where the tissue exudate sample contains one or more analytes representing a state of the tissue. The one or more analytes are isolated from the exudate sample on a substrate. The exudate is transferred from the substrate to an immunoassay. The immunoassay is illuminated with photons, where the illuminating comprises a controlled photon exposure. Light emanating from the immunoassay is imaged, where the imaging captures intensities of light wavelengths across the light wavelength spectrum. A signature for the one or more analytes is generated, based on analysis of the intensities that were imaged. The signature expresses a magnitude for each of the one or more analytes. A wound assessment is generated based on the signature. Tissue wound healing is modeled based on the signature. A tissue treatment plan is generated based on the signature. The light emanating from the immunoassay that is imaged can be based on fluorescence, reflection, absorption, and so on.

Fluorophores with different emission spectra can be distinguished based on comparison of their infrared (IR), Red-Green-Blue (RGB), and long-wavelength IR (LWIR) emission signals. A fluorescence signal can be spectrally resolved using filters common to many digital imagers. The digital imagers can include color digital imagers such as the Red, Green, and Blue Bayer filters, IR imagers, thermal imagers, and so on. The imagers can be integrated in typical, inexpensive sensors such as RGB sensors that are the basis of common color digital imagers. These sensors generally demonstrate peak blue sensitivity at 400-475 nm, peak green sensitivity at 475-580 nm, and peak red sensitivity at 580-750 nm. One or more optical excitation sources can be provided to the excitation light wavelength bands. In a usage example, an optical excitation source at a wavelength is provided near the edge of, or slightly inside or outside of, the RGB visible light wavelength spectrum, such as at 405 nm. However, it should be noted that the definition of the exact wavelengths of visible light is somewhat subjective. For purposes of discussion, a visible light wavelength range of about 425 nm-725 nm is understood herein, although discrete wavelengths or wavelength ranges are used when possible. The optical excitation source wavelength can, when used to illumine a material sample, elicit a fluorescence response from the material sample that can be detected by a sensor such as an RGB sensor, a thermal sensor, an IR sensor, and so on. In order to prevent cross talk from the excitation source into the spectral channels detected by the one or more imagers, the excitation source may be outfitted with a bandpass filter. This technique can be especially useful if the excitation source exhibits a long “red-side” tail into the longer wavelengths detectable by the RGB or other sensor. Additionally, a long-pass filter placed in front of the sensor can prevent spurious signals from the excitation source, such as an LED, from reaching the sensor.

The low-cost, portable method of exudate analysis using optical signatures disclosed herein can use ordinary, readily available, sensors such as a Red-Green-Blue (RGB) sensor. The RGB sensor typically is mass produced and has applications in low-cost technology that endeavors to detect light waves in the visible spectrum in a standard three-color, RGB palette suitable for digital processing. Other low-cost sensors can include IR sensors, thermal sensors, and so on. The RGB sensor typically employs an integrated Bayer filter applied during the manufacturing process of a CMOS, CCD, or similar sensor semiconductor fabrication. The Bayer filter is completely integrated into the sensor and cannot be removed, replaced, or adjusted. When light impinges the surface of an RGB sensor, the underlying photosensors register a signal related to the intensity of the impinging wavelengths as a function of the color of the integrated sensor directly over each photosensor device. The disclosed technology does not require expensive filter wheels, complex optical alignments, or stationary, non-handheld components.

FIG. 1 is a flow diagram for exudate analysis using optical signatures. Access to a tissue exudate sample is obtained, where the tissue exudate sample contains one or more analytes representing a state of the tissue. The one or more analytes are isolated from the exudate sample on a substrate. The exudate is transferred from the substrate to an immunoassay. The immunoassay is illuminated with photons, where the illuminating comprises a controlled photon exposure. Light emanating from the immunoassay is imaged, where the imaging captures intensities of light wavelengths across the light wavelength spectrum. The imaging is accomplished using an imaging sensor. A signature for the one or more analytes is generated, based on analysis of the intensities that were imaged. Since no filter wheels are needed to filter the response to illumination of the immunoassay with photons, and because the components can generally be obtained at low cost, the tissue exudate sample analysis techniques disclosed within can be implemented in a handheld unit.

The flow 100 includes obtaining access to a tissue exudate sample 110, where the tissue exudate sample contains one or more analytes representing a state of the tissue. Exudate can include a liquid that is emitted by skin pores, a wound, and so on. The tissue exudate sample that is obtained can contain wound tissue, water, fibrin, glucose, immune cells, platelets, proteins, growth factors, chemokines, cytokines, proteases, metabolic waste, microorganisms, wound debris, dead cells, blood, infectious agents, blood serum, plasma, and so on. The exudate can be derived from blood and interstitial fluid. In embodiments, the tissue exudate can be collected on an absorbent material. The exudate can include transudate. The wound exudate can be obtained from a bandage associated with a patient, beneath a film, from a negative pressure system, and so on. The flow 100 includes isolating 120 the one or more analytes from the exudate sample on a substrate. The analytes can include cells, enzymes, proteins, mediators, chemokines, cytokines, growth factors, proteases, inhibitors, receptors, and so on, and can be associated with the state or condition of the wound. Various substrates can be used. In embodiments, the substrate can be integrated into a bandage placed over the tissue. In embodiments, the isolating can include extracting both analytes and colonizing microbial agents. Since the wound may be infected, knowing which microbial agents may be colonizing the wound can help inform treatment of the wound in general and the infection in particular. The flow 100 includes using a lateral flow assay 126 to accomplish the isolating. A lateral flow assay can operate based on passing a liquid over a pad or substrate that has been treated with reactive molecules. The isolation can occur because exudate flow in the assay helps spatially separate the analytes and allows them to be bound to antibodies and then fixed in position by another antibody. The isolating can be accomplished using a variety of techniques. In the flow 100, the isolating can be accomplished using a single-step 122 process. Isolating analytes from an exudate sample in one step can be accomplished using an integrated bandage, described later. In the flow 100, the isolating can be accomplished using a two-step 124 process. Isolating analytes from an exudate sample in two steps can be accomplished using a cassette transfer operation, described later. In embodiments, the isolating can associate the one or more analytes to one or more light emitting or light absorbing markers. Thus, the presence or absence of a given analyte can be determined based on fluoresced, reflected, or absorbed light from the one or more markers. In other embodiments, the isolating can enable spatial separation of the one or more analytes. The separation of the analytes can be used to determine the locations of the analytes within the wound exudate sample. In embodiments, the spatial separation can enable tissue spatial registration. Tissue spatial separation can include a location within a wound such as a wound edge or perimeter, a wound center, a wound bed, and the like. In embodiments, the tissue spatial registration can enable tracking of additional tissue exudate samples over time. The spatial registration can enable tracking of healing, stalled healing, or nonhealing of the wound. In embodiments, the tracking augments a tissue treatment plan. In embodiments, the exudate that was obtained can be transferred to the substrate using a transfer foam or woven material.

Embodiments include transferring the exudate from the substrate to an immunoassay. An immunoassay can include a biochemical test that can measure the concentration of or the presence of a molecule. The molecule can include a macromolecule, a small molecule, and so on. The detected molecule or analyte can be detected based on techniques that include using antibodies or perhaps antigens. In embodiments, the immunoassay can be a system of lateral flow assays, enzyme-linked immunosorbent assays (ELISAs), immunohistochemistry assays, Western blot assays, flow cytometry assays, dot blot assays, multiplexed assays using encoded particles, and so on. The transferring can be accomplished using a variety of techniques. In embodiments, the transferring of the exudate from the substrate to an immunoassay is performed using a cartridge to apply mechanical pressure to extract the exudate from the substrate. The flow 100 includes extracting unbound non-analyte molecules 130 from the substrate. The unbound non-analyte molecules can include molecules unassociated with a wound such as debris in the wound. The extracting the non-analyte molecules can be accomplished using one or more techniques. In embodiments, the extracting can include magnetic or electrostatic extraction. Such a technique can be useful for removing non-analyte molecules that are magnetic or electrostatically charged. In other embodiments, the extracting can include fluidic washing. In the flow 100, the extraction is accomplished using a series of proteases 132. A protease is an enzyme that can be used to break down proteins and peptides. In embodiments, a protease can be specific to a single amino acid sequence and can be activated by a parameter associated a wound. The wound parameters can include biochemical species such as cells, enzymes, proteins, mediators, chemokines, cytokines, growth factors, proteases, inhibitors, receptors, and so on, as well as healing stages such as hemostasis, infected, inflamed, granulating, epithelializing, remodeling, and so on.

The flow 100 includes illuminating the immunoassay with photons 140, where the illuminating comprises a controlled photon exposure. The photos that are used to illuminate the immunoassay can include photons from one or more optical excitation light wavelength bands. The optical excitation light wavelength bands can include infrared (IR) bands, visible light bands (e.g., red, green, blue, or RGB), long-wavelength IR (LWIR) bands, thermal bands, and so on. In embodiments, a first band of the plurality of optical excitation light wavelength bands can include wavelengths substantially in the range of 325 nm to 375 nm, a second band of the plurality of optical excitation light wavelength bands can include wavelengths substantially in the range of 350 nm to 400 nm, and a third band of the plurality of optical excitation light wavelength bands can include wavelengths substantially in the range of 375 nm to 425 nm. Other bands can also be used. In other embodiments, a fourth band of the plurality of optical excitation light wavelength bands comprises wavelengths substantially in the range of 400 nm to 450 nm. The optical excitation light wavelength bands can include wide bands or narrow bands. In embodiments, the plurality of optical excitation light wavelength bands can include narrow bands substantially at 350 nm, 375 nm, 400 nm, 425 nm, 450 nm, 500 nm, 525 nm, 550 nm, 575 nm, 600 nm, and 625 nm. In embodiments, the controlled photon exposure can include ambient lighting on the substrate. The ambient light can include visible light or RGB light. In other embodiments, the controlled photon exposure can include one or more fluorescence excitation light wavelength bands such as the fluorescence excitation light wavelength band described previously.

The flow 100 includes imaging light emanating from the immunoassay 150, One or more sensors, such as an IR or LWIR sensor, an RGB sensor, a thermal sensor, etc., can be used to detect the light emanating from the immunoassay. In embodiments, the imaging captures reflected light, where the reflected light can include light within any of the bandwidths mentioned throughout. In other embodiments, the imaging captures fluorescent emanating light. The imaging light can be based on fluoresced, reflected, or absorbed light. The light that is emitted can be associated with light emitting markers. In embodiments, the one or more light emitting markers emit photons in a fluorescent or a phosphorescent manner. In the flow 100, the imaging captures intensities of light wavelengths across the light wavelength spectrum 152. The light wavelength spectrum can include IR light, long-wavelength IR (LWIR) light, visible light, RGB light, UV light, and so on. The electromagnetic radiation emanating from the immunoassay can include heat.

The flow 100 includes generating a signature 160 for the one or more analytes, based on analysis of the intensities that were imaged. The signature can be based on numerical values, a range of values, ratios, percentages, qualitative evaluations, and so on. In embodiments, the signature expresses a magnitude for each of the one or more analytes. The signature that is generated can be applied to a variety of purposes. The flow 100 includes generating a wound assessment 162 based on the signature. The wound assessment can include a severity of the wound such as minor, moderate, or severe; a healing state for the wound such as healing, stalled healing, or nonhealing; an infection state for the wound such as infected or not infected; and so on. In embodiments, the wound state includes a stalled state, a healing state, a nonhealing state, an infected state, an inflamed state, a granulating state, or an epithelializing state. The assessment can also include other parameters such as surgery indicated, drug therapy required, etc. The flow 100 further includes modeling tissue wound healing 164 based on the signature. The modeling can simulate wound healing. The flow 100 includes generating a tissue treatment plan 166 based on the signature. The tissue treatment plan can include recommended cleaning and bandaging techniques, surgical recommendations, drug therapy recommendations, and the like. Embodiments can include regenerating the output signature over time. The regenerating the output signature can be performed based on updated parameter values associated with a wound, changes in fluorescence response, changes in absorption response, and the like. The regenerating the output signature over time can be used to determine whether a wound is healing properly, is healing slowly, is not healing, and so on. In embodiments, the regenerating the output signature over time can inform a wound care treatment plan. The wound care treatment plan can include therapies such as medicinal therapies, surgery, and so on.

Various steps in the flow 100 may be changed in order, repeated, omitted, or the like without departing from the disclosed concepts. Various embodiments of the flow 100 can be included in a computer program product embodied in a non-transitory computer readable medium that includes code executable by one or more processors.

FIG. 2 is a flow diagram for isolating. Wound tissue exudate can contain analytes, colonizing microbial agents, and so on. Various isolation techniques can be used to isolate one or more analytes, microbes, etc., from a tissue exudate sample on a substrate. The isolating enables identification of the analytes, microbes, and other constituents within the exudate for purposes including wound assessment, infection type identification, wound treatment, and so on. The one or more isolating techniques enable exudate analysis using optical signatures. Access to a tissue exudate sample is obtained. The tissue exudate sample contains analytes representing a state of the tissue. The analytes are isolated from the substrate to an immunoassay. The immunoassay is illuminated with a controlled exposure to photons. Light emanating from the immunoassay is imaged using an image sensor. The imaging captures intensities of light wavelengths across the light wavelength spectrum. A signature for the one or more analytes is generated. The signature expresses a magnitude for each of the analytes.

The flow 200 includes isolating the one or more analytes 210 from the exudate sample on a substrate. In the context of analytes within an exudate associated with a wound, the analytes can include molecules of interest such as saccharides and proteins. The saccharides and proteins can include glucan, IL1β, IL6, TNF, pH, MMP1, MMP2, MMP8, MMP9, MMP13, TGFβ1, Angiopoietin-1, Angiopoietin-2, Angiogenin, endostatin, CD105, CD31, GM-CSF, TIMP1-4, hyaluronic acid, Collagens I/III/IV, IL10, VEGF, HB-EGF, EGF, PDGF, and so on. In embodiments, the isolating can be accomplished using a lateral flow array. In the flow 200, the isolating comprises extracting both analytes and colonizing microbial agents 220. A wound, particularly a wound that is healing slowly or not healing, may or may not be infected. To determine whether a wound is infected and if so by what, determination of the colonizing microbial agents is critical to planning an appropriate treatment for the wound. In the flow 200, the isolating is accomplished using a series of proteases 222. A protease is an enzyme that can be used to break down proteins and peptides. In embodiments, a protease can be specific to a single amino acid sequence and can be activated by a parameter associated a wound. The wound parameters can include biochemical species such as cells, enzymes, proteins, mediators, chemokines, cytokines, growth factors, proteases, inhibitors, receptors, and so on, as well as healing stages such as hemostasis, infected, inflamed, granulating, epithelializing, remodeling, and so on.

The flow 200 includes using a series of fluorescent reporters 224. A fluorescent reporter can be used to measure gene expression in a cell or in a series of cells. A fluorescent reporter can be specific to a single protease and can be acted on by the single protease. The protease can change the magnitude of the fluorescent component of the reporter and the polarization anisotropy signal of the reporter. In the flow 200, the absorption and emission channels for each reporter within the series of reporters are chosen so that each reporter can be spectrally resolved 226 to augment analysis. Spectral resolution includes choosing reporters that absorb and emit light within excitation bands that are sufficiently separated to be clearly identified. The flow 200 includes enabling binding of analytes to a substrate 228. The binding of analytes to a substrate can be accomplished using one or more substrate adhesion molecules (SAMs). A SAM can include a protein that binds a cell to a substrate. Some of the amino acids that make up the SAM bind to the cell, while other amino acids bind to the substrate. In the flow 200 an array comprising an antibody membrane 230 captures and identifies target molecules or molecules of interest. In embodiments, the capturing and identifying can include extracting unbound non-analyte molecules from the substrate. The extracting the unbound non-analyte molecules from the substrate can be accomplished by fluidic washing. In other embodiments, the extracting can include magnetic or electrostatic extraction.

Discussed through, assaying of exudate obtained from a wound can be used to determine a state of the wound, whether or not the wound is infection, and a treatment plan for a wound. Note however that different locations within a wound can heal at different rates. As a result, assaying two or more locations associated with a wound can further inform wound treatment. In the flow 200, the isolating enables spatial separation 232 of the one or more analytes. The spatial separation of the analytes can indicate the presence or the absence of one or more analytes at various locations within the wound. Thus, successful treatment of the wound can be augmented by determining the locations of the analytes within the wound. In embodiments, the spatial separation can enable tissue spatial registration. In the flow 200, the tissue spatial registration enables tracking of additional tissue exudate samples 234 over time. The amount of time can include a testing period such as hours, days, or weeks; a series of medical appointments at which exudate samples can be collected; and so on. In embodiments, the tracking augments a tissue treatment plan. Through spatial registration, various locations and/or features of a wound (or other tissue) can be tracked over time to determine healing trajectories for those particular locations and/or features.

Various steps in the flow 200 may be changed in order, repeated, omitted, or the like without departing from the disclosed concepts. Various embodiments of the flow 200 can be included in a computer program product embodied in a non-transitory computer readable medium that includes code executable by one or more processors.

FIG. 3 shows a system block diagram for diagnosis and treatment. Discussed throughout, signatures such as optical signatures associated one or more analytes can be generated based on scanning one or more light wavelength bands on a material sample such as a wound sample. The signatures can be generated to enable exudate analysis. The exudate analysis can include determining a wound location, assaying the exudate from the wound to identify infection, determining healing progress, and so on. Using optical signatures enables exudate analysis. Access to a tissue exudate sample is obtained, where the tissue exudate sample contains one or more analytes representing a state of the tissue. The one or more analytes are isolated from the exudate sample on a substrate. The exudate is transferred from the substrate to an immunoassay. The immunoassay is illuminated with photons, where the illuminating comprises a controlled photon exposure. Light emanating from the immunoassay is imaged, where the imaging captures intensities of light wavelengths across the light wavelength spectrum. A signature for the one or more analytes is generated, based on analysis of the intensities that were imaged.

The wound healing process is complex. There are in excess of 13 critical parameters local to the wound that control the healing process, and if not at correct levels can stall healing indefinitely. These parameters include but are not limited to: collagens, glucan, IL1β, IL6, TNF, pH, MMP1, MMP2, MMP8, MMP9, MMP13, TGFβ1, Angiopoietin-1, Angiopoietin-2, Angiogenin, endostatin, CD105, CD31, GM-CSF, TIMP1-4, hyaluronic acid, Collagens I/III/IV, IL10, VEGF, HB-EGF, EGF, PDGF, fibroblasts, water, hyaluronic acid, interleukins, angiogenesis factors, porphyrins, pyoverdines, lipofuscin, and metabolic factors such as NADH and FAD. Because the process is dynamic, these parameters change over time. In addition, the wound is not homogenous, and the parameters vary by location, as well.

Wounds will not heal properly or at all if there is an infection. In general, infections are caused by microbes that can populate the wound and grow at an exponential rate. While these microbes are present to some degree in all wounds and skin surfaces, they are harmful to wound healing when they reach a critical population and virulence that they begin to induce injury in the host. That is, infection is not just the presence of bacteria, but also the presence of a host response and injury. It is this inflammatory response that can interrupt the native healing process, allow further propagation of the microbe or pathogen, and result in deterioration of the wound to an acute or chronic state. This deterioration process can cascade, with the initial infection allowing the wound to decline to a point where additional microbes can contaminate, colonize, and infect the wound. As a result, the compromised wound is trapped in a state of chronic nonhealing or further deterioration. Currently, there is no clinical technique for determining the presence, abundance and/or location of infecting microbes and the resulting host inflammatory responses. Technology that could identify the site of infection and inflammation and help assess the presence or absence of infecting microbes would meet an unmet need in the clinic.

Host responses like what is seen with infection can also be caused by autoimmune disorders (no infecting microbes) such as pyoderma gangrenosum. Pyoderma gangrenosum is thought to be an immune response to injury, and the treatment (immune suppression) is different from microbial infections and therefore requires careful diagnosis. Once the infection has been identified and treated, over 50% of all chronic wounds still do not heal, even when there is no infection. This is because one of more of the critical wound parameters or vital signs is not in the correct range. Disruptions to the wound healing process may be related to excess or lack of biochemical species. For example, fibroblasts may be producing collagen only for it to be destroyed by an excess of collagenase created by another cell or biochemical process, resulting in stalled healing. A precise balance of cells, extra-cellular matrix, and biochemicals are necessary for wound healing. Accurately measuring the relative abundance of these components can call for targeted treatments to repair the underlying healing mechanisms.

Precision medicine techniques for skin diagnostics can be used to identify whether one or more critical parameters such as wound parameters are within ranges which enable healing or not. The one or more wound parameters are associated with the skin diagnostics. Based on the assessed parameters, one or more treatments can be recommended that address results of diagnostics such as wound locating, wound treatment, treatment efficacy, and so on. The system block diagram 300 includes an infection screener 310. The infection screener can include an imaging component which can be used to locate infection. The infection can include a skin infection, a respiratory infection, residual cancer, and so on. In embodiments, the infection can include a COVID-19 infection. The system block diagram 300 can include an assay component such as an exudate analyzer 320. The assay component can include a lab-based component, a bedside component, and so on. In the block diagram 300, data associated with the infection screener and data associated with the exudate analyzer can be provided to a precision treatment platform 330. The precision treatment platform can use the imaging data from the infection screener to perform infection location 332. The infection location can be associated with skin, sinuses, or lungs; a wound; and the like. The precision treatment platform can use the exudate analysis data to generate a wound biology model 334. Based on the infection location and the wound biology model, an infection treatment component 340 can be used to propose infection treatment. The proposed infection treatment can be presented as an array (described below). The infection treatment component can rank treatments to determine a most appropriate treatment for an individual patient.

Infection location can be accomplished non-invasively using a combination of fluorescence and reflectance images generated at specific excitation and emission wavelengths. Cellular and molecular species exist in the wound and peri-wound areas. The fluorescence and reflectance images can exhibit spectral signatures, where the spectral signatures can be compared to known spectral signatures. The spectral signatures can be extracted, calculated, and analyzed, and can be used to identify signatures including infection signatures, healing signatures, nonhealing signatures, and the like. A variety of techniques can be used for locating infection, whether the infection is associated with a wound, a respiratory infection, a COVID-19 infection, residual cancer detection, and so on. Discussed above and throughout, infection detection can be accomplished using a handheld device, a cart-based device, etc. The detection can be based on fluorescence measurements, absorption measurements, reflection measurements, and/or transmission measurements, or any combination of measurements thereof. The detection can further be based on absorption and reflection of various excitation light wavelength bands by tissue such as wound tissue, and it can be augmented by fluorescence measurements.

With regard to wound healing measurements, it is important to note that about half of chronic wounds are not infected. These wounds are chronic and slow healing due to an imbalance of healing factors, mostly related to poor blood supply and elevated protease activity, which destroys needed proteinaceous signals required for healing. There are numerous treatments that attempt to address this, but there can be ten to twenty factors that work together to foster healing. Further, no single treatment addresses all of them. Key wound factors, signaling pathways, and immigrant and resident dermal cells coordinating reparative and regenerative responses post-injury are discussed below. The imager can assess a number of key biomarkers, but additional analysis may be necessary to fully assess a wound. The analysis can require extraction and assessment of wound exudate.

FIG. 4 is a table for identifying infection. Identifying that an infection is present, and determining the type of infection, can be critical to treating the infection, promoting healing of a wound, and so on. Identifying infection is based on exudate analysis, where the exudate analysis is based on optical signatures. Access to a tissue exudate sample is obtained, where the tissue exudate sample contains one or more analytes representing a state of the tissue. The one or more analytes are isolated from the exudate sample on a substrate, and the exudate is transferred from the substrate to an immunoassay. The immunoassay is illuminated with photons, and light emanating from the immunoassay is imaged. A signature for the one or more analytes is generated, based on analysis of the intensities that were imaged.

Table 400 shows example wound parameters that can be determined based on scanning a material sample such as a skin sample using a plurality of optical excitation light wavelength bands. The table can include one or more parameters 410 and values 412 associated with the one or more parameters. The parameters can include temperature, porphyrin, vasculature/blood flow, collagen, cellular activity, pH, and so on. The values associated with the one or more parameters can include a numerical value, a range of values, a percentage, a quality, an assessment, and so on. Table 400 shows qualitative values or assessments assigned to the one or more parameters. Based on the optical excitation light wavelength scans of the skin sample, infection can be determined from high temperature, high porphyrin, low vasculature/blood flow, low collagen, high cellular activity, high pH, etc.

FIG. 5 is a system block diagram for infection locating. A patient can present with one or more indications that can be associated with an infection. Locating the infection can be critical to providing appropriate care to the patient to help her recover from the infection. Locating an infection can be associated with locating a wound or other damage to the skin of the patient. Other infections, such as respiratory infections and COVID-19 infections, and detection of residual cancer, among others, can be harder to locate or identify because the infections or residual cancer are likely not visible. In these and other cases, optical techniques may be applied to infection locating. The infection locating enables exudate analysis using optical signatures. Access to a tissue exudate sample is obtained, where the tissue exudate sample contains one or more analytes representing a state of the tissue. The one or more analytes are isolated from the exudate sample on a substrate. The exudate is transferred from the substrate to an immunoassay. The immunoassay is illuminated with photons, where the illuminating comprises a controlled photon exposure. Light emanating from the immunoassay is imaged, where the imaging captures intensities of light wavelengths across the light wavelength spectrum. A signature for the one or more analytes is generated, based on analysis of the intensities that were imaged.

The system block diagram 500 includes a hyperspectral or multispectral imager 510. The multispectral imager can be based on a handheld component, a mobile cart-based component, and so on. The multispectral imager can receive data from one or more cameras (discussed below) and can measure fluorescence, absorption, and reflection of wound tissue at a variety of optical excitation light wavelength bands. The multispectral imager can be coupled to a processor 512. The processor can control illumination sources, filters, cameras, sensors, and so on. The processor or processors can execute code, where the code can perform various operations associated with the infection detection. The code can include code for control, image processing, data analysis, etc. The processor can be used to isolate signals from biochromes associated with infection. The signal isolation from biochromes associated with infection can be accomplished by scanning a material sample with one or more optical excitation light wavelength bands. The excitation wavelength can be held constant while one or more signals are collected from progressively longer wavelength emission bands. In embodiments, the multispectral imager can collect and isolate signals associated with nicotinamide adenine dinucleotide plus hydrogen (NADH) and flavins by collecting 440-500 and 500-550 nm emission photons, respectively, and scanning excitation (325-375 nm, 350-400 nm, 375-425 nm, 400-450 nm).

The multispectral imager can be used to locate infection associated with a patient 520. The infection can include an infection associated with a material sample such as skin, a respiratory infection, a particular infection such as a COVID-19 infection, residual cancer detection, and so on. The infection location can be accomplished using a handheld scanner, a cart-based scanner, and the like, as discussed throughout. The multispectral imager can be coupled to a variety of components including illumination sources, filters, cameras, and so on. The system block diagram 500 includes a visible light camera and filters 530. The camera can include an imaging sensor, where the imaging sensor can detect wavelengths within the visible light band. The visible light band can include one or more wavelengths between 380 nm and 700 nm. The visible light filters can include one or more of a red filter, a green filter, a blue filter, etc. The system block diagram 500 includes an infrared light camera and filters 532. The infrared camera, which can be based on an infrared imaging sensor, can detect wavelengths within the infrared band. The infrared band can include wavelengths between 780 nm and 1 mm. The infrared filters can be used to capture or isolate one or more wavelength bands within the infrared band. The system block diagram 500 can include illumination and filters 534. The illumination can be based on a plurality of optical excitation light wavelength bands, where the light wavelength bands can include visible light, IR light, long wavelength infrared (LWIR) light, and so on. The filters can include one or more filters which can be used to provide specific optical excitation light wavelengths. The system block diagram 500 can include a thermal (LWIR) camera 536. As noted throughout, detection of infection can include detection of elevated temperature or a “hot spot” on a material sample such as a skin sample. In the system block diagram 500, the illumination and filters can be used to provide a plurality of optical excitation light wavelength bands that can be scanned on a material sample. The material sample, such as a skin sample, a body part, a limb, exudate, and so on, can be associated with the patient 520.

FIG. 6 is a system block diagram for dermis healing. Dermis healing can be based on performing wound healing measurements, where the wound healing measurements can be based on exudate analysis. While some chronic wounds may not be infected, they can remain chronic or can be slow to heal. The slow healing can be due a variety of factors such as poor blood supply, elevated protease activity, and so on. The latter can destroy proteinaceous signals that are required for healing. The dermis healing can be improved by exudate analysis using optical signatures. Access is obtained to a tissue exudate sample that contains one or more analytes representing a state of the tissue. The analytes are isolated from the exudate sample on a substrate, and the exudate is transferred from the substrate to an immunoassay. The immunoassay is illuminated with photons, and light emanating from the immunoassay is imaged. A signature is generated for the one or more analytes, based on analysis of the imaged intensities.

In order to determine a treatment that is best suited to a wound such as an infected wound, a variety of factors can be determined. These factors, which in embodiments can include ten to twenty factors, can work together to promote healing. Typically, no one treatment addresses all of the factors. The system block diagram 600 shows a basic overview of key factors associated with a wound, signaling pathways, and immigrant and resident dermal cells that can coordinate reparative and regenerative responses of wound healing. A wound image can be analyzed and wound exudate can be analyzed to determine one or more biomarkers. The wound exudate can be obtained from a bandage associated with a patient, beneath a film, present in a negative pressure system, and so on. The wound exudate can be analyzed in a laboratory, a bed-side assay, etc. In embodiments, an assay array can be used to detect molecules of interest to determine wound healing. The molecules of interest can include key saccharides and proteins such as glucan, IL1β, IL6, TNF, pH, MMP1, MMP2, MMP8, MMP9, MMP13, TGFβ1, Angiopoietin-1, Angiopoietin-2, Angiogenin, endostatin, CD105, CD31, GM-CSF, TIMP1-4, hyaluronic acid, Collagens I/III/IV, IL10, VEGF, HB-EGF, EGF, PDGF, and so on.

In the system block diagram 600, an individual's insult and resulting innate and adaptive immune responses can stimulate microvascular leakage, signaling neutrophils and monocyte/macrophages to a wound site 610. Glucan synthesis 620 can occur and support inflammatory macrophages 622. In addition, hyaluronic acid synthesis 640 can occur and repair macrophages are borne 642. Transforming growth factor beta (TGF B) can be released from repair macrophages 630 and affect fibroblasts at the wound site. Platelets, fibroblasts, and vascular cells contribute to platelet-derived growth factor (PDGF) 628 and several other growth factor production, e.g. FGF, VEGF, etc. Fibroblasts, vascular cells, and macrophages produce protease matrix metalloproteinases (MMPs) 626, which are affected by the local pH 624. The fibroblasts and vascular cells can also influence hyaluronic acid synthesis 640 and the production of collagen 638. The pH 634 can also affect microbial proliferation, oxygen (O2) 636 levels, which have a bearing on collagen synthesis, and basement membrane assembly (when pH is optimal for healing). The collagen 638 affects blood vessels 646 as well. Repair macrophages 642 can in turn affect both PDGF 628 and vascular endothelial growth factor (VEGF) 644. Thus even the basic overview dermis healing system block diagram 600 shows how complex the process is.

FIG. 7 is a system block diagram for antibody detection. An array such as the array shown in 700 can be used for antibody detection. Antibody detection can be used to identify molecules such as glucan, IL1β, IL6, TNF, pH, MMP1, MMP2, MMP8, MMP9, MMP13, TGFβ1, Angiopoietin-1, Angiopoietin-2, Angiogenin, endostatin, CD105, CD31, GM-CSF, TIMP1-4, hyaluronic acid, Collagens I/III/IV, IL10, VEGF, HB-EGF, EGF, PDGF, and so on. The molecules can also be detected using other techniques including mass spectrometry, nuclear magnetic resonance (NMR), chromatography, fluorescence spectroscopy, absorption spectroscopy, antibody assays, polarization anisotropy assays, zymography, fluorescence-activated cell sorting (FACS), gel electrophoresis, and the like. Antibody detection enables exudate analysis using optical signatures. Access to a tissue exudate sample is obtained, where the tissue exudate sample contains one or more analytes representing a state of the tissue. The one or more analytes are isolated from the exudate sample on a substrate. The exudate is transferred from the substrate to an immunoassay. The immunoassay is illuminated with photons, where the illuminating comprises a controlled photon exposure. Light emanating from the immunoassay is imaged, where the imaging captures intensities of light wavelengths across the light wavelength spectrum. A signature for the one or more analytes is generated, based on analysis of the intensities that were imaged.

The system block diagram for antibody detection 700 includes a light source 710. The light source can include a plurality of optical excitation light wavelength bands, where the wavelength bands can include visible light, IR light, LWIR light (heat), and so on. Bioluminescence can be created using horseradish peroxidase (HRP) and hydrogen peroxide. The bioluminescence can be detected by a camera, photographic film, etc. Streptavidin 720 can be used to bind to a biotin 730 with strong affinity. A detection antibody 740 can be in a specific and known location on a material sample such as skin, on a patient's body part, and so on. Thus, light due to bioluminescence or the emission from a fluorophore can be emitted from the specific and known location can indicate that a target analyte 750 has been captured 760. In embodiments, indication that the target antibody has been captured can be based on parameters such as vital signs associated with the wound (WVS). A blocked membrane 770 can be used to support the antibody detection array. The blocked membrane can be used to capture and identify target molecules.

FIG. 8 illustrates an antibody array. An antibody array can show one or more wound parameters or vital signs associated with a wound. The antibody array can be determined for one or more locations associated with a wound such as a wound perimeter, a wound center, etc. The antibody array enables exudate analysis using optical signatures. Access to a tissue exudate sample that contains one or more analytes representing a state of the tissue is obtained. The analytes are isolated from the exudate sample on a substrate, and the exudate is transferred from the substrate to an immunoassay. The immunoassay is illuminated with a controlled exposure of photons. Light emanating from the immunoassay is imaged, where the imaging captures intensities of light wavelengths across the light wavelength spectrum. A signature for the one or more analytes is generated, based on analysis of the intensities that were imaged.

Antibody arrays are shown for a wound center 800 and a wound perimeter 802. The antibody arrays can be based on analysis results of wound fluid or exudate, i.e., a liquid biopsy collected from the wound center 810, wound perimeter 850, and so on. Such assays can be performed to determine the state of healing of a wound based on the absence or presence, together with the relative abundance of one or several wound controllers, classifiers or variables controlling healing stages and wound state. Such assays are useful for gauging healing of a wound such as a slow-healing wound, because the rate of healing of the wound can vary across the wound. Fourteen parameters are shown for the example assays of exudate at the wound center and the wound perimeter. More or fewer parameters may be used for the comparison of assay results. The parameters can include Activin A 812 and 852; Angiopoietin 1 and Ang 2 814 and 854; and Amphiregulin 816 and 856. Note the difference between the assay results 816 and 856. This difference can indicate that the perimeter of the wound is healing while the center of the wound is not healing or is only slowly healing. The parameters can further include Endostatin/Collagen XVIII 818 and 858; Fibroblast Growth Factors (FGF) FGF 1 and FGF 2 820 and 860; Glial cell line-derived neurotrophic factors (GDNF) and Granulocyte-macrophage colony-stimulating factors (GM-CSF) 822 and 862. The factors can further include Heparin-binding epidermal growth factor-like (HB-EGF) factors 824 and 864; Insulin-like growth factor-binding proteins (IGFBP) IGFBP 1 and IGFBP 2 826 and 866; Interleukin 1 Beta 828 and 868; and Transforming growth factor betas (TGFb-1) 830 and 870. The factors can also include Monocyte chemoattractant protein 1 (MCP-1) 832 and 872; Matrix metalloproteinases (MMPs) MMP8 and MMP9 834 and 874; Tissue inhibitors of metallopeptidase (TIMP) TIMP1 and TIMP4 836 and 876; and Vascular endothelial growth factors (VEGF) 838 and 878. As noted above, one or more factors can be present or absent at a wound location such as a wound center, a wound perimeter, and so on. Note further that the magnitude of a given parameter can vary across the wound, temporally and spatially, and that these amplitude modulations influence the stage of healing and the wound state, while classifying each. Such differences in magnitude can also be indicative of causes for a wound to be slow healing or nonhealing.

FIG. 9 shows images for infection detection and analysis of wound state. An image or a series of images can be obtained and analyzed for infection detection. The images can be based on fluorescence, reflection, absorption, and so on, of a material sample such as tissue scanned with one or more optical excitation light wavelength bands. The images enable exudate analysis using optical signatures. Access to a tissue exudate sample is obtained, where the tissue exudate sample contains one or more analytes representing a state of the tissue. The one or more analytes are isolated from the exudate sample on a substrate. The exudate is transferred from the substrate to an immunoassay. The immunoassay is illuminated with photons, wherein the illuminating comprises a controlled photon exposure. Light emanating from the immunoassay is imaged, where the imaging captures intensities of light wavelengths across the light wavelength spectrum. A signature is generated for the one or more analytes, based on analysis of the intensities that were imaged.

Images which have been collected and analyzed can be used for infection detection 900. The images can be based on fluorescence response wavelengths, absorption response wavelengths, and so on, where the response wavelengths can be emitted by the material sample in response to exposer by the various optical excitation light wavelength bands. Note that the emitted response wavelengths can be different from the excitation light wavelengths scanned on the material sample. In embodiments, a first band of the plurality of optical excitation light wavelength bands can include wavelengths substantially in the range of 325 nm to 375 nm, a second band of the plurality of optical excitation light wavelength bands can include wavelengths substantially in the range of 350 nm to 400 nm, and a third band of the plurality of optical excitation light wavelength bands can include wavelengths substantially in the range of 375 nm to 425 nm. Other bands of optical excitation light wavelength bands can further be used. In embodiments, a fourth band of the plurality of optical excitation light wavelength bands can include wavelengths substantially in the range of 400 nm to 450 nm. An output signature can be interpreted from emission detected from the scanned material sample. In embodiments, the interpreting can be based on measured wavelengths substantially in the range of 400 nm to 460 nm. Other fluorescence excitation light wavelength bands can be used to expose the material sample. Further embodiments include exposing the material sample to a fluorescence excitation light wavelength band comprising wavelengths substantially in the 315 nm to 375 nm range to augment the interpreting. Image 910 can be based on 375 nm excitation with 430 nm emission, where the 430 nm emission or output signature can be indicative of the presence of collagen.

Image 912 can be based on 375 nm excitation with 470 nm output signature can be indicative of the presence of nicotinamide adenine dinucleotide plus hydrogen (NADH) and flavins. An image can include photograph 914. The photograph can be based on visible light, where visible light can include wavelengths substantially within the approximate range of 380 nm and 750 nm. The images can be based on absorption. Image 916 can be based on 570 nm absorption, where the 570 nm absorption can be indicative of hemoglobin. The images can further be based on narrow bands. In embodiments, the plurality of optical excitation light wavelength bands can include narrow bands substantially at 350 nm, 375 nm, 400 nm, 425 nm, 450 nm, 500 nm, 525 nm, 550 nm, 575 nm, 600 nm, and 625 nm. Other embodiments can include exposing the material sample to a narrow fluorescence excitation light wavelength band comprising wavelengths substantially at 400 nm to augment the interpreting. The interpreting can be based on additional measured wavelengths. In embodiments, the interpreting can be based on measured wavelengths substantially in the range of 600 nm to 660 nm and 675 nm to 725 nm. Image 918 can be based on 425 nm excitation and 650 nm emission which can be analyzed to generate an output signature. In embodiments, the output signature can be indicative of the presence of porphyrins. Longer wavelengths can also be used to analyze the material sample. Image 920 can be based on the magnitude of photons between 7 and 15 microns that are detected, which can create a monochromatic image where intensity is converted into temperature, and where the intensity represents a thermal profile of the wound. In embodiments, the interpreting is based on excitation wavelengths from 380 nm to 420 nm and measured wavelengths substantially in the range of 500 nm to 550 nm and 550 nm to 600 nm. In embodiments, the output signature is indicative of the presence of pyoverdine, based on a ratio of output values from the range of 550 nm to 600 nm to output values from the range of 500 nm to 550 nm.

FIG. 10 is a table showing biochromes and fluorescent channels. A fluorophore is a chemical compound that when excited by light re-emits light. Biochromes include substances such as chemical compounds which present a color based on selective absorption of other colors. The colors are associated with wavelengths of light. Biochromes and fluorescent channels support exudate analysis using optical signatures. Access to a tissue exudate sample that contains one or more analytes representing a state of the tissue is obtained. The analytes are isolated from the exudate sample on a substrate. The exudate is transferred from the substrate to an immunoassay. The immunoassay is illuminated with photons, where the illuminating includes a controlled photon exposure. Light emanating from the immunoassay is imaged, and a signature for the one or more analytes is generated, based on analysis of the intensities that were imaged.

A table based on biochromes and fluorescent channels is shown 1000. The table includes skin fluorophores and biochromes 1010. Each of the skin fluorophores and biochromes can correspond to a factor associated with healing. Each of the factors can further be associated with one or more biomolecules or cell localizations 1012. The various skin fluorophores and biochromes can be excited by an optical excitation light wavelength band 1014. The excited fluorophores and biochromes generate an emission response 1016 by the scanned material sample. In embodiments, the material sample can include cells, tissues, and organs. The material sample can include skin, lungs, and so on. The emission response can be indicative of infection such as infection of a wound, respiratory infection such as a COVID-19 infection or influenza infection, residual cancer detection, and so on.

FIG. 11 is a table showing cells associated with hemostasis and wound healing. A wound to skin, an organ, and so on, can cause prodigious bleeding. The first step to healing the wound is to stanch the bleeding. Hemostasis is a process that stops bleeding and prevents further bleeding based on blood platelet function and coagulation of blood, where coagulation includes transforming blood from a liquid to a gel. The coagulating or clotting of the blood is dependent on functional blood platelets, which become activated, releasing many factors that control downstream effectors, which influence vascular leakage, immune responses and the reparative/regenerative responses needed for healing. Hemostasis and wound healing can be analyzed using exudate analysis using optical signatures. Access to a tissue exudate sample is obtained, where the tissue exudate sample contains one or more analytes representing a state of the tissue. The one or more analytes are isolated from the exudate sample on a substrate. The exudate is transferred from the substrate to an immunoassay. The immunoassay is illuminated with photons, where the illuminating comprises a controlled photon exposure. Light emanating from the immunoassay is imaged, where the imaging captures intensities of light wavelengths across the light wavelength spectrum. A signature is generated for the one or more analytes, based on analysis of the intensities that were imaged.

Table 1100 shows various cells that can be associated with hemostasis and the various stages and state of wound healing. The table shows resident cells 1110, where the resident cells can be present in blood, tissue, and so on. The resident cells can produce key products 1112, where the key products can signal and modulate healing. The healing can include healing of a wound such as a tissue wound or an organ wound; recovery from an infection such as an infection of the skin or organ, or a respiratory infection such as COVID-19 or influenza; detection to facilitate removal of residual cancer; and so on. The key products can be associated with target cell or cell function 1114. The target cell or cells can be associated with wound healing, infection recovery, and the like.

FIG. 12 is a table showing immune surveillance cells. The immune system associated with an individual fights “foreign invaders” to their body. The foreign invaders can include bacteria, fungi, viruses, tumors, and so on. The immune system identifies and attempts to eliminate the invading pathogen(s), whether fungi, bacteria, viruses, etc. based on immune surveillance. For example, a tumor can include cells that are based on transformed normal cells. The transformed cells associated with tumor-expressed antigens, where the expressed antigens are not found in normal cells. As a result, the body attacks with immune cells the self-antigens as ‘foreign’ antigens. Immune surveillance can be analyzed using exudate analysis using optical signatures. Access to a tissue exudate sample is obtained, where the tissue exudate sample contains analytes representing a state of the tissue. The analytes are isolated from the exudate sample on a substrate, and the exudate is transferred from the substrate to an immunoassay. The immunoassay is illuminated with a controlled photon exposure. A signature for the one or more analytes is generated, based on analysis of the intensities that were imaged.

A table showing immune surveillance cells, key products, and one or more target cells is shown 1200. Some symptoms or conditions presented by a patient can appear similar to those caused by infection, but can actually be caused by autoimmune disorders, as above. One identifier that differentiates between an infection and an autoimmune disorder can include an absence of infecting microbes or non-specific inflammation, e.g., vasculitis, which is associated with the autoimmune disorder (e.g. gangrenosum pyoderma). Careful diagnosis can be required to differentiate between an autoimmune disorder, which may be treated with an immune suppression technique, and an infection which may be treated by boosting immunity, prescribing antibiotics, and so on. Various immune surveillance cells are shown 1210. The cells can be associated with one or more key products 1212. The key products can be used to elicit effector or target cell function 1214, where the target cells can be attacked, used to fight infection, used to rebuild tissue, and so on.

FIG. 13 shows granulation identification. Granulation identification can enable exudate analysis using optical signatures. Access to a tissue exudate sample is obtained, where the tissue exudate sample contains one or more analytes representing a state of the tissue. The one or more analytes are isolated from the exudate sample on a substrate, and the exudate is transferred from the substrate to an immunoassay. The immunoassay is illuminated with photons, and light emanating from the immunoassay is imaged. A signature for the one or more analytes is generated, based on analysis of the intensities that were imaged.

In the graph 1300, an x-axis indicating wavelength 1310 is provided. Increasing wavelength from left to right indicates decreasing frequency of light waves and a traversal from the ultraviolet spectrum, approximately sub-400 nm, through the blue, green, and red wavelength regions, roughly 450 nm, 550 nm, and 650 nm, respectively, to the infrared wavelength band, which is roughly greater than 750 nm. It should be noted that an exact wavelength definition of a particular color is somewhat arbitrary and is dependent on the sensor type. For example, the cones of a human eye roughly sense RGB signals using three cone types, but they are generally distributed differently from a typical CMOS RGB sensor's output. However, maintaining a consistent definition for a given system is generally required in order to provide consistent sample indications. The graph 1300 also includes a left y-axis of absorption amount 1312 and a right y-axis of transmission amount 1314.

The graph 1300 includes absorption characteristics, such as absorption characteristic 1322, typical for the presence of collagen, absorption characteristic 1324, typical for the presence of hemoglobin (Hgb), and absorption characteristic 1326, typical for the presence of oxygenated hemoglobin (oxyHb). The typical absorption characteristics 1322, 1324, and 1326 can be used as reference signals as is, or they can be compensated to enable generation of an indication of material composition. A granulation output signature is isolated by quantifying the dip in the Hgb spectrum at 450 nm, illustrated in highlight circle 1342. Tissue that is mostly collagen will not have a dip, whereas granulation tissue will have a dip that resides roughly halfway between the typical Hgb characteristic 1324 and/or 1326 and the typical collagen characteristic 1322. The intensity of the dip can be quantified by taking the ratio or difference of the absorption intensity at 1336 and/or 1338 and comparing it to the absorption intensity at 1334 and/or 1332.

The graph 1300 shows signals indicative of filter characteristics, including signals 1332, 1334, 1336, and 1338. Signal 1332 represents a light wavelength centered at about 488 nm with a bandwidth of about 10 nm and a relative transmission amplitude of about 0.7 out of 1. Signal 1334 represents a light wavelength centered at about 520 nm with a bandwidth of about 40 nm and a relative transmission amplitude of almost 1.0 out of 1. Signal 1336 represents a light wavelength centered at about 550 nm with a bandwidth of about 10 nm and a relative transmission amplitude of about 0.6 out of 1. Signal 1338 represents a light wavelength centered at about 570 nm with a bandwidth of about 10 nm and a relative transmission amplitude of about 0.5 out of 1. It is to be understood that the characteristics and signals illustrated herein have substantially the values shown in graph 1300, but that normal, typical variations and equipment calibration may provide a delta to the characteristics and signals, such as a five percent delta.

FIG. 14 illustrates water identification. Water identification can enable exudate analysis using optical signatures. Access to a tissue exudate sample is obtained, where the tissue exudate sample contains one or more analytes representing a state of the tissue. The one or more analytes are isolated from the exudate sample on a substrate, and the exudate is transferred from the substrate to an immunoassay. The immunoassay is illuminated with photons, and light emanating from the immunoassay is imaged. A signature for the one or more analytes is generated, based on analysis of the intensities that were imaged.

In the graph 1400, an x-axis indicating wavelength 1410 is provided. Increasing wavelength from left to right indicates decreasing frequency of light waves and a traversal from the ultraviolet spectrum, roughly sub-400 nm, through the blue, green, and red wavelength regions, roughly 450 nm, 550 nm, and 650 nm, respectively, to the infrared wavelength band, which is roughly greater than 750 nm. It should be noted that an exact wavelength definition of a particular color is somewhat arbitrary and dependent on the sensor type. For example, the cones of a human eye roughly sense RGB signals using three cone types, but they are generally distributed differently from a typical CMOS RGB sensor's output. However, maintaining a consistent definition for a given system is generally required in order to provide consistent sample indications. The graph 1400 also includes a left y-axis of absorption amount 1412 and a right y-axis of transmission amount 1414.

The graph 1400 includes absorption characteristics, such as absorption characteristic 1422, indicative of the presence of collagen, absorption characteristic 1424, indicative of the presence of hemoglobin (Hgb), absorption characteristic 1426, indicative of the presence of oxygenated hemoglobin (oxyHb), and absorption characteristic 1428, indicative of the presence of water. The typical absorption characteristics 1422, 1424, 1426, and 1428 can be used as reference signals as is, or they can be compensated to enable generation of an indication of material composition. A water output signature is isolated by irradiating a material sample (wound or other) with broad-band white light and comparing the absorption at 960 nm (or similar) and 800 nm (or similar). In the graph 1400, broad-band white light is passed by a long-pass filter, shown as signal 1434, which cuts off wavelengths of light below 450 nm (in the ultraviolet range), and allows visible light above 450 nm with a relative transmission amplitude of about 0.9 out of 1. Light emanating from the sample can be measured at two or more points at successively longer wavelengths, as shown by signals 1436 and 1438. Signal 1436 represents an optical filter centered at about 800 nm with a bandwidth of about 20 nm and a relative amplitude of about 0.85 out of 1. Signal 1438 represents a light wavelength centered at about 960 nm with a bandwidth of about 100 nm and a relative amplitude of about 0.85 out of 1. The output signature of water will be substantially higher at the longer wavelength sample point. As shown in graph 1400, this is not true for the absorption characteristics of collagen 1422 and hemoglobin 1424 and 1426 as sampled at 800 nm and 960 nm. It is to be understood that the characteristics and signals have substantially the values illustrated in graph 1400, but that normal, typical variations and equipment calibration may provide a delta to the characteristics and signals, such as a five percent delta.

FIG. 15 shows blood vessel identification. Blood vessel identification can enable exudate analysis using optical signatures. Access to a tissue exudate sample is obtained, where the tissue exudate sample contains one or more analytes representing a state of the tissue. The one or more analytes are isolated from the exudate sample on a substrate, and the exudate is transferred from the substrate to an immunoassay. The immunoassay is illuminated with photons, and light emanating from the immunoassay is imaged. A signature for the one or more analytes is generated, based on analysis of the intensities that were imaged.

In the graph 1500, an x-axis indicating wavelength 1510 is provided. Increasing wavelength from left to right indicates decreasing frequency of light waves and a traversal from the ultraviolet spectrum, roughly sub-400 nm, through the blue, green, and red wavelength regions, roughly 450 nm, 550 nm, and 650 nm, respectively, to the infrared wavelength band, which is roughly greater than 750 nm. It should be noted that an exact wavelength definition of a particular color is somewhat arbitrary and dependent on the sensor type. For example, the cones of a human eye roughly sense RGB signals using three cone types, but they are generally distributed differently from a typical CMOS RGB sensor's output. However, maintaining a consistent definition for a given system is generally required in order to provide consistent sample indications. The graph 1500 also includes a left y-axis of absorption amount 1512 and a right y-axis of transmission amount 1514.

The graph 1500 includes absorption characteristics, such as absorption characteristic 1522, indicative of the presence of hemoglobin (Hgb), and absorption characteristic 1524, indicative of the presence of oxygenated hemoglobin (oxyHb). The typical absorption characteristics 1522 and 1524 can be used as reference signals as is, or they can be compensated to enable generation of an indication of material composition. A blood vessel signal is isolated based on the absorption of Hgb at 523 nm and 660 nm. Light from two different light emitting diodes (LEDs) is used to illumine a material sample. In the graph 1500, signal 1532 represents the typical output spectrum of a 523 nm LED, and signal 1534 represents the typical output spectrum of a 660 nm LED. As can be seen in graph 1500, the absorption characteristics of Hgb 1522 and oxyHb 1524 are very similar at about 523 nm. However, an order of magnitude difference is observed when comparing absorption characteristics 1522 and 1524 at 660 nm. The low absorption in the red band is indicative of oxygenated hemoglobin, which is typically found in active blood vessels, but not found in pooled blood due to bruising or other wound-related phenomena. It is to be understood that the characteristics and signals have substantially the values illustrated in graph 1500, but that normal, typical variations and equipment calibration may provide a delta to the characteristics and signals, such as a five percent delta.

FIG. 16 illustrates tissue oximetry. Tissue oximetry can enable exudate analysis using optical signatures. Access to a tissue exudate sample is obtained, where the tissue exudate sample contains one or more analytes representing a state of the tissue. The one or more analytes are isolated from the exudate sample on a substrate, and the exudate is transferred from the substrate to an immunoassay. The immunoassay is illuminated with photons, and light emanating from the immunoassay is imaged. A signature for the one or more analytes is generated, based on analysis of the intensities that were imaged.

In the graph 1600, an x-axis indicating wavelength 1610 is provided. Increasing wavelength from left to right indicates decreasing frequency of light waves and a traversal from the ultraviolet spectrum, roughly sub-400 nm, through the blue, green, and red wavelength regions, roughly 450 nm, 550 nm, and 650 nm, respectively, to the infrared wavelength band, which is roughly greater than 750 nm. It should be noted that an exact wavelength definition of a particular color is somewhat arbitrary and dependent on the sensor type. For example, the cones of a human eye roughly sense RGB signals using three cone types, but they are generally distributed differently from a typical CMOS RGB sensor's output. However, maintaining a consistent definition for a given system is generally required in order to provide consistent sample indications. The graph 1600 also includes a left y-axis of absorption amount 1612 and a right y-axis of transmission amount 1614.

The graph 1600 includes absorption characteristics, such as absorption characteristic 1622, indicative of the presence of hemoglobin (Hgb), and absorption characteristic 1624, indicative of the presence of oxygenated hemoglobin (oxyHb). The typical absorption characteristics 1622 and 1624 can be used as reference signals as is, or they can be compensated to enable generation of an indication of material composition. An oxygenated tissue output signature is isolated by comparing absorption at 960 nm, where oxyHb absorption dominates, to 650 nm, where Hgb absorption dominates. In the graph 1600, broad-band white light is passed by a long-pass filter, shown as signal 1634, which cuts off wavelengths of light below 450 nm (in the ultraviolet range), and allows visible light above 450 nm with a relative transmission amplitude of about 0.9 out of 1. Light emanating from the sample can be measured at two or more points at successively longer wavelengths, as shown by signals 1636 and 1638. Signal 1636 represents an optical filter centered at about 650 nm with a bandwidth of about 100 nm and a relative amplitude of about 0.95 out of 1. Signal 1638 represents a light wavelength centered at about 960 nm with a bandwidth of about 100 nm and a relative amplitude of about 0.85 out of 1. The output signature of oxygenated tissue will show higher absorption at the longer wavelength sample point. It is to be understood that the characteristics and signals have substantially the values illustrated in graph 1600, but that normal, typical variations and equipment calibration may provide a delta to the characteristics and signals, such as a five percent delta.

FIG. 17 shows a diagram for a substrate isolating analytes from an exudate sample in one step. Isolating analytes from an exudate sample in one step can enable exudate analysis using optical signatures. Access to a tissue exudate sample is obtained, where the tissue exudate sample contains one or more analytes representing a state of the tissue. The one or more analytes are isolated from the exudate sample on a substrate, and the exudate is transferred from the substrate to an immunoassay. The immunoassay is illuminated with photons, and light emanating from the immunoassay is imaged. A signature is generated for the one or more analytes, based on analysis of the intensities that were imaged.

One step diagram 1700 shows a wound bed 1710 within skin 1712 or some other tissue structure. The wound bed 1710 is covered by an absorbent material 1722, such as a bandage, a woven material, a foam material, and so on. The absorbent material 1722 is in contact with the wound bed 1710, which allows exudate from the wound to flow from the wound bed 1710 through the absorbent material 1722, through an opening in hydrophobic polymer 1713 and 1714, into lateral flow assay 1742, and finally into absorbent material 1740 and 1741 at the end of the lateral flow immunoassay 1742, as indicated by exudate flow arrows 1724 and 1726. Included in absorbent material 1740 can be pH indicator 1746. Included in absorbent material 1741 can be pH indicator 1744. Transparent windows 1736 and 1738 can allow optical analysis of the exudate as it flows through the assay 1742, driven by capillary forces as well as the hydrostatic pressure of the wound. Reagent for the assay can be added via reagent port 1734 or by reagent reservoirs embedded in the hydrophobic polymer 1713 and 1714 (not shown). Thus, a substrate comprising absorbent material 1722, hydrophobic polymer 1713 and 1714, lateral flow assay 1742, absorbent material 1740 and 1741, optional pH indicators 1744 and 1746, reagent port 1734, and transparent windows 1736 and 1738 can enable isolating analytes from an exudate sample in one step. The time elapsed for the process of exudate flow and assay isolation will vary based on the patient, the wound type, the exact materials and pore size, etc., but it can be in the range of 5 to 30 minutes. The absorbent material will carry many times its weight in exudate. The analytes that are isolated in lateral flow assay 1742 can then be optically analyzed through transparent windows 1736 and 1738. Of course, it is to be appreciated that the one step diagram 1700 represents a vertical cross-sectional view, and that the wound bed, substrate, and described features exist in three-dimensions. Isolating analytes from an exudate sample in one step can comprise an integrated, or “smart”, bandage for exudate analysis using optical signatures.

FIG. 18 shows a diagram for a substrate isolating analytes from an exudate sample in two or more steps. Isolating analytes from an exudate sample in two or more steps can enable exudate analysis using optical signatures. Access to a tissue exudate sample is obtained, where the tissue exudate sample contains one or more analytes representing a state of the tissue. The one or more analytes are isolated from the exudate sample on a substrate, and the exudate is transferred from the substrate to an immunoassay. The immunoassay is illuminated with photons, and light emanating from the immunoassay is imaged. A signature is generated for the one or more analytes, based on analysis of the intensities that were imaged.

Multistep diagram 1800 illustrates the first step of the multistep process and shows a wound bed 1810 within skin 1812 or some other tissue structure. The wound bed 1810 is covered by an absorbent material 1822, such as a foam material, although other absorbent materials are possible. The absorbent material 1822 is in contact with the wound bed 1810, which allows exudate from the wound to flow from the wound bed 1810 to the absorbent material 1822 as illustrated by arrows 1824. Region 1826 of illustrates that an amount of exudate has been transferred from the wound bed 1810 to the absorbent material 1822. The exudate flow illustrated in diagram 1800 can be driven by capillary forces as well as by the hydrostatic pressure of the wound. Other methods to enhance exudate flow into the absorbent material, such as negative pressure (suction) over the wound bed and absorbent material, are possible. A soaking time of several minutes to more than an hour might be necessary to allow enough exudate to penetrate the absorbent material. However, a typical time for soaking can be about ten minutes. After sufficient soaking time, absorbent material 1822 can be taken off of wound bed 1810.

Multistep diagram 1802 illustrates a second step of the multistep process, whereby soaked absorbent material 1832 is carefully placed in a cassette 1814, so as not to prematurely squeeze the exudate 1834 out of the soaked absorbent material 1832. The impermeable (or semi-impermeable) and rigid (or semi-rigid) cassette allows the soaked absorbent material 1832 to transfer exudate 1834 to a lateral flow immunoassay 1842 through opening 1818 of cassette top piece 1816, as indicated by exudate flow arrows 1826. The flow of exudate 1834 into the lateral flow assay 1842 is facilitated by pressing cassette top piece 1816 into cassette 1814, as illustrated. The lateral flow assay 1842 can be attached to cassette top piece 1816 to further facilitate exudate flow. In due time, lateral flow assay 1842 can be appropriately positioned for optical analysis as described herein, either by removing lateral flow assay 1842 from cassette top piece 1816, or by removing cassette top piece 1816 from cassette 1814 with lateral flow assay 1842 still attached, or by positioning cassette 1814 with cassette top piece 1816 and lateral flow assay 1842 still in place. The time elapsed for the process of exudate flow and assay isolation will vary based on the amount of exudate 1834 collected in the soaked absorbent material 1832, the amount of pressure applied to the cassette top piece 1816 and or lateral flow assay 1842, the material properties of the assay, and so on. A typical time for analyte isolation by the assay can be in the range of 3 to 10 minutes.

FIG. 19 is a system diagram for exudate analysis using optical signatures. The system 1900 can include one or more processors 1910, which are attached to a memory 1912 which stores instructions. The system 1900 can further include a display 1914 coupled to the one or more processors 1910 for displaying data, indications of sample analysis, directions, input requests, control options, excitation wavelengths, filter options, compensation options, data forwarding options, and so on. Embodiments of the system 1900 comprise a computer system for exudate analysis comprising: one or more processors 1910 that are coupled to the memory 1912 which stores instructions, wherein the one or more processors, when executing the instructions which are stored, are configured to: obtain access to a tissue exudate sample, wherein the tissue exudate sample contains one or more analytes representing a state of the tissue; isolate the one or more analytes from the exudate sample on a substrate; transfer the exudate from the substrate to an immunoassay; illuminate the immunoassay with photons, wherein the illuminating comprises a controlled photon exposure; image light emanating from the immunoassay, wherein the imaging captures intensities of light wavelengths across the light wavelength spectrum; and generate a signature for the one or more analytes, based on analysis of the intensities that were imaged.

The system 1900 can include an obtaining component 1920. The obtaining component 1920 can be used to obtain access to a tissue exudate sample, where the tissue exudate sample contains one or more analytes representing a state of the tissue. The tissue exudate sample can be obtained using a variety of techniques including gathering exudate from a bandage that may have been covering a wound, swabbing the wound, extracting liquid from the wound, extracting liquid from below a film covering the wound, using a negative pressure device, and so on. The tissue exudate sample that is obtained can contain wound tissue, water, fibrin, glucose, immune cells, platelets, proteins, growth factors, metabolic waste, microorganisms, wound debris, dead cells, blood, infectious agents, blood serum, plasma, and so on. The exudate can be derived from blood and interstitial fluid. In embodiments, the exudate that was obtained can be transferred to a substrate using a transfer foam or woven material. The system 1900 can include an isolating component 1930. The isolating component 1930 can be used to isolate the one or more analytes from the exudate sample on a substrate. The isolating can be used to isolate further constituents within the exudate. In embodiments, the isolating can include extracting both analytes and colonizing microbial agents. The isolating can be used to determine which analytes are present as well as which of the one or more varieties of colonizing microbial agents are present. Determining the microbial agents is critical to effective treatment of the wound. Further embodiments include extracting unbound non-analyte molecules from the substrate. A variety of techniques can be used for the extracting. In embodiments, the extracting can include magnetic or electrostatic extraction. Chemical and liquid techniques can also be used for the extracting. In embodiments, the extracting can include fluidic washing.

The isolating can be accomplished using a variety of techniques. In embodiments, the isolating can be accomplished using a lateral flow array. In a lateral flow array, liquid is passed across a material such as a pad on which reactive molecules have been placed. The reactive molecules are used to indicate a visual result, such as a positive result or a negative result. In embodiments, the isolating can associate the one or more analytes to one or more light emitting markers. Thus, a given light marker can include the presence or absence of an analyte. The markers can produce light based on one or more physical or chemical techniques. In embodiments, the one or more light emitting markers can emit photons in a fluorescent or a phosphorescent manner. In order for the markers to be detected or seen more easily, the markers can be distributed across the isolating pad. In embodiments, the isolating enables spatial separation of the one or more analytes. As a further benefit of the isolating, the spatial separation enables tissue spatial registration.

The system 1900 can include a transferring component 1940. The transferring component 1940 can be used to transfer the exudate from the substrate to an immunoassay. The transferring can be accomplished using one or more techniques. In embodiments, the transferring of the exudate from the substrate to an immunoassay can be performed using a cartridge. The cartridge can be used to apply mechanical pressure to the substrate to extract the exudate from the substrate. In order to extract the exudate from the substrate, the exudate must first have been transferred to the substrate. An immunoassay can include a biochemical test that can measure the concentration of or the presence of a molecule. The molecule can include a macromolecule, a small molecule, and so on. The detected molecule or analyte can be detected based on techniques that include using antibodies or perhaps antigens. The system 1900 can include an illuminating component 1950. The illuminating component 1950 can be used to illuminate the immunoassay with photons, wherein the illuminating comprises a controlled photon exposure. Various types of lights, wavelengths and bands of light, and so on can be used for the controlled photon exposure. In embodiments, the controlled photon exposure can include ambient lighting on the substrate. The ambient lighting can be based on visible light. In other embodiments, the controlled photon exposure can include one or more fluorescence excitation light wavelength bands.

The system 1900 can include an imaging component 1960. The imaging component 1960 can be used to image light emanating from the immunoassay, where the imaging captures intensities of light wavelengths across the light wavelength spectrum. The imaging can be accomplished using an imaging sensor, where the imaging sensor can include an IR sensor, a long-wavelength IR (LWIR) sensor, an RGB sensor, a thermal sensor, and so on. In embodiments, the imaging captures reflected light. The reflected light can result from the controlled photon exposure based on ambient lighting. In other embodiments, the imaging captures fluorescent emanating light. The fluorescent emanating light can result from the controlled photon exposure comprising one or more fluorescence excitation light wavelength bands. The system 1900 can include a generating component 1970. The generating component 1970 can be used to generate a signature for the one or more analytes, based on analysis of the intensities that were imaged. The signature that is generated can be used for a variety of purposes. In embodiments, the signature can express a magnitude for each of the one or more analytes. The magnitudes of the analytes can be used to determine various wound parameters or wound “vital signs”. Further embodiments can include generating a wound assessment based on the signature. The wound assessment can be used for a variety of wound-related assessments, treatments, and so on. In embodiments, the wound assessment can indicate a wound treatment plan. The wound treatment plan can include cleaning and rebandaging protocols, drug therapies, surgery, etc. In other embodiments, the wound assessment can include a wound state. A wound state can include a condition of a wound, a rate of healing of the wound, whether the wound is healing, and so on. In embodiments, the wound state includes a stalled state, a healing state, a nonhealing state, an infected state, an inflamed state, a granulating state, or an epithelializing state. The wound assessment can further indicate the size and shape of the wound. In embodiments, the wound assessment can indicate a wound topography. In embodiments, the wound topography can include a wound center, a wound perimeter, or an array of wound zones.

The system 1900 can include a computer program product embodied in a non-transitory computer readable medium for exudate analysis, the computer program product comprising code which causes one or more processors to perform operations of: obtaining access to a tissue exudate sample, wherein the tissue exudate sample contains one or more analytes representing a state of the tissue; isolating the one or more analytes from the exudate sample on a substrate; transferring the exudate from the substrate to an immunoassay; illuminating the immunoassay with photons, wherein the illuminating comprises a controlled photon exposure; imaging light emanating from the immunoassay, wherein the imaging captures intensities of light wavelengths across the light wavelength spectrum; and generating a signature for the one or more analytes, based on analysis of the intensities that were imaged.

Each of the above methods may be executed on one or more processors on one or more computer systems. Embodiments may include various forms of distributed computing, client/server computing, and cloud-based computing. Further, it will be understood that the depicted steps or boxes contained in this disclosure's flow charts are solely illustrative and explanatory. The steps may be modified, omitted, repeated, or re-ordered without departing from the scope of this disclosure. Further, each step may contain one or more sub-steps. While the foregoing drawings and description set forth functional aspects of the disclosed systems, no particular implementation or arrangement of software and/or hardware should be inferred from these descriptions unless explicitly stated or otherwise clear from the context. All such arrangements of software and/or hardware are intended to fall within the scope of this disclosure.

The block diagrams and flowchart illustrations depict methods, apparatus, systems, and computer program products. The elements and combinations of elements in the block diagrams and flow diagrams, show functions, steps, or groups of steps of the methods, apparatus, systems, computer program products and/or computer-implemented methods. Any and all such functions—generally referred to herein as a “circuit,” “module,” or “system”—may be implemented by computer program instructions, by special-purpose hardware-based computer systems, by combinations of special purpose hardware and computer instructions, by combinations of general-purpose hardware and computer instructions, and so on.

A programmable apparatus which executes any of the above-mentioned computer program products or computer-implemented methods may include one or more microprocessors, microcontrollers, embedded microcontrollers, programmable digital signal processors, programmable devices, programmable gate arrays, programmable array logic, memory devices, application specific integrated circuits, or the like. Each may be suitably employed or configured to process computer program instructions, execute computer logic, store computer data, and so on.

It will be understood that a computer may include a computer program product from a computer-readable storage medium and that this medium may be internal or external, removable and replaceable, or fixed. In addition, a computer may include a Basic Input/Output System (BIOS), firmware, an operating system, a database, or the like that may include, interface with, or support the software and hardware described herein.

Embodiments of the present invention are limited to neither conventional computer applications nor the programmable apparatus that run them. To illustrate: the embodiments of the presently claimed invention could include an optical computer, quantum computer, analog computer, or the like. A computer program may be loaded onto a computer to produce a particular machine that may perform any and all of the depicted functions. This particular machine provides a means for carrying out any and all of the depicted functions.

Any combination of one or more computer readable media may be utilized including but not limited to: a non-transitory computer readable medium for storage; an electronic, magnetic, optical, electromagnetic, infrared, or semiconductor computer readable storage medium or any suitable combination of the foregoing; a portable computer diskette; a hard disk; a random access memory (RAM); a read-only memory (ROM), an erasable programmable read-only memory (EPROM, Flash, MRAM, FeRAM, or phase change memory); an optical fiber; a portable compact disc; an optical storage device; a magnetic storage device; or any suitable combination of the foregoing. In the context of this document, a computer readable storage medium may be any tangible medium that can contain or store a program for use by or in connection with an instruction execution system, apparatus, or device.

It will be appreciated that computer program instructions may include computer executable code. A variety of languages for expressing computer program instructions may include without limitation C, C++, Java, JavaScript™, ActionScript™, assembly language, Lisp, Perl, Tcl, Python, Ruby, hardware description languages, database programming languages, functional programming languages, imperative programming languages, and so on. In embodiments, computer program instructions may be stored, compiled, or interpreted to run on a computer, a programmable data processing apparatus, a heterogeneous combination of processors or processor architectures, and so on. Without limitation, embodiments of the present invention may take the form of web-based computer software, which includes client/server software, software-as-a-service, peer-to-peer software, or the like.

In embodiments, a computer may enable execution of computer program instructions including multiple programs or threads. The multiple programs or threads may be processed approximately simultaneously to enhance utilization of the processor and to facilitate substantially simultaneous functions. By way of implementation, any and all methods, program codes, program instructions, and the like described herein may be implemented in one or more threads which may in turn spawn other threads, which may themselves have priorities associated with them. In some embodiments, a computer may process these threads based on priority or other order.

Unless explicitly stated or otherwise clear from the context, the verbs “execute” and “process” may be used interchangeably to indicate execute, process, interpret, compile, assemble, link, load, or a combination of the foregoing. Therefore, embodiments that execute or process computer program instructions, computer-executable code, or the like may act upon the instructions or code in any and all of the ways described. Further, the method steps shown are intended to include any suitable method of causing one or more parties or entities to perform the steps. The parties performing a step, or portion of a step, need not be located within a particular geographic location or country boundary. For instance, if an entity located within the United States causes a method step, or portion thereof, to be performed outside of the United States then the method is considered to be performed in the United States by virtue of the causal entity.

While the invention has been disclosed in connection with preferred embodiments shown and described in detail, various modifications and improvements thereon will become apparent to those skilled in the art. Accordingly, the foregoing examples should not limit the spirit and scope of the present invention; rather it should be understood in the broadest sense allowable by law. 

What is claimed is:
 1. A method for exudate analysis comprising: obtaining access to a tissue exudate sample, wherein the tissue exudate sample contains one or more analytes representing a state of the tissue; isolating the one or more analytes from the exudate sample on a substrate; transferring the exudate from the substrate to an immunoassay; illuminating the immunoassay with photons, wherein the illuminating comprises a controlled photon exposure; imaging light emanating from the immunoassay, wherein the imaging captures intensities of light wavelengths across the light wavelength spectrum; and generating a signature for the one or more analytes, based on analysis of the intensities that were imaged.
 2. The method of claim 1 wherein the signature expresses a magnitude for each of the one or more analytes.
 3. The method of claim 1 where the immunoassay is a system of lateral flow assays, enzyme-linked immunosorbent assays (ELISA), or multiplexed assays using encoded particles.
 4. The method of claim 1 wherein the controlled photon exposure comprises ambient lighting on the substrate.
 5. The method of claim 1 wherein the imaging captures reflected light.
 6. The method of claim 1 wherein the controlled photon exposure comprises one or more fluorescence excitation light wavelength bands.
 7. The method of claim 6 wherein the imaging captures fluorescent emanating light.
 8. The method of claim 1 wherein the tissue exudate is collected on an absorbent material.
 9. The method of claim 8 wherein the transferring of the exudate from the substrate to an immunoassay is performed using a cartridge to apply mechanical pressure to extract the exudate from the substrate.
 10. The method of claim 1 wherein the tissue exudate sample comprises wound tissue, blood, infectious agents, blood serum, or plasma.
 11. The method of claim 10 further comprising generating a wound assessment based on the signature.
 12. The method of claim 11 wherein the wound assessment indicates a wound treatment plan.
 13. The method of claim 11 wherein the wound assessment includes a wound state.
 14. The method of claim 13 wherein the wound state includes a stalled state, a healing state, a nonhealing state, an infected state, an inflamed state, a granulating state, or an epithelializing state.
 15. The method of claim 11 wherein the wound assessment indicates a wound topography.
 16. The method of claim 15 wherein the wound topography includes a wound center, a wound perimeter, or an array of wound zones.
 17. The method of claim 1 wherein the isolating comprises extracting both analytes and colonizing microbial agents.
 18. The method of claim 1 wherein the isolating is accomplished using a lateral flow array. 19-20. (canceled)
 21. The method of claim 1 wherein the isolating enables spatial separation of the one or more analytes.
 22. The method of claim 21 wherein the spatial separation enables tissue spatial registration.
 23. The method of claim 22 wherein the tissue spatial registration enables tracking of additional tissue exudate samples over time.
 24. The method of claim 23 wherein the tracking augments a tissue treatment plan.
 25. The method of claim 1 further comprising modeling tissue wound healing based on the signature.
 26. The method of claim 1 further comprising generating a tissue treatment plan based on the signature.
 27. The method of claim 1 wherein the substrate is integrated into a bandage placed over the tissue.
 28. The method of claim 1 wherein the exudate that was obtained is transferred to the substrate using a transfer foam or woven material. 29-31. (canceled)
 32. A computer program product embodied in a non-transitory computer readable medium for exudate analysis, the computer program product comprising code which causes one or more processors to perform operations of: obtaining access to a tissue exudate sample, wherein the tissue exudate sample contains one or more analytes representing a state of the tissue; isolating the one or more analytes from the exudate sample on a substrate; transferring the exudate from the substrate to an immunoassay; illuminating the immunoassay with photons, wherein the illuminating comprises a controlled photon exposure; imaging light emanating from the immunoassay, wherein the imaging captures intensities of light wavelengths across the light wavelength spectrum; and generating a signature for the one or more analytes, based on analysis of the intensities that were imaged.
 33. A computer system for exudate analysis comprising: a memory which stores instructions; one or more processors coupled to the memory wherein the one or more processors, when executing the instructions which are stored, are configured to: obtain access to a tissue exudate sample, wherein the tissue exudate sample contains one or more analytes representing a state of the tissue; isolate the one or more analytes from the exudate sample on a substrate; transfer the exudate from the substrate to an immunoassay; illuminate the immunoassay with photons, wherein the illuminating comprises a controlled photon exposure; image light emanating from the immunoassay, wherein the imaging captures intensities of light wavelengths across the light wavelength spectrum; and generate a signature for the one or more analytes, based on analysis of the intensities that were imaged. 